Are you ready at ToThePoint?
Building a reinforcement learning simulation of the smart autonomous trash bin.
In another internship we are building a prototype of smart trashcan with necessary sensors to check if it needs to be emptied. When it is time to be emptied it should place itself in a central position for the cleaning personnel to handle.
Description of the assignment
- The aim of this internship is to build the office in a gaming environment (Unity) and then use reinforcement learning to make the autonomous drive to the central position where the cleaning personnel can pick it up.
Goals
- The autonomous drive itself should be challenging enough to cope with moving objects and displacement of objects, such as chairs that get in its trajectory or a person walking by.
What you will gain
- Learn how to design an end-to-end data processing pipeline
- AND put this in production
- Gain knowledge about steam processing
- Gain knowledge and experience in machine learning
- You will get to know Hadoop
- You will gain experience in powerful visualization libraries such as D3.js
- That lovely feeling you get knowing your design will be effectively used in production
What you need
- You have a shown interest in a challenging but instructive assignment
- You’d like to explore Machine Learning and stream processing techniques
- Using Spark, Python or Scala does not scare you at all
- You know what ReactJS is, or are eager to learn
- You like to learn about data visualization
- You like to learn a heck of a lot on a relatively short period of time
Technologies you'll be using
- Reinforcement learning
- Unity
- Tensorflow
- Python
Location of your assignment
Veldkant 33B, 2550 Kontich
Your mentor
Kevin Smeyers – Technical lead machine learning ToThePoint
